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SpEED: fast computation of sensitive spaced seeds
Lucian Ilie1, Silvana Ilie, Anahita Mansouri Bigvand
1Department of Computer Science, University of Western Ontario, London, ON N6A 5B7, Canada. ilie@csd.uwo.ca
Bioinformatics (Oxford, England)
|June 22, 2011
Summary
Spaced seeds are key for bioinformatics similarity searches. A new software, SpEED, efficiently computes highly sensitive spaced seeds, outperforming existing tools in speed and quality for applications like sequence alignment.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Multiple spaced seeds are the current standard for similarity searches in bioinformatics.
- Applications include sequence alignment, read mapping, and oligonucleotide design.
- Existing software for computing spaced seeds has limitations in speed and sensitivity.
Purpose of the Study:
- To introduce SpEED, a novel software program for computing multiple spaced seeds.
- To demonstrate SpEED's capability in generating highly sensitive spaced seeds.
- To compare SpEED's performance against existing state-of-the-art software.
Main Methods:
- Development of the SpEED software algorithm.
- Implementation of SpEED for computing multiple spaced seeds.
- Benchmarking SpEED against leading existing software programs for speed and seed quality.
Main Results:
- SpEED computes highly sensitive multiple spaced seeds.
- SpEED demonstrates significant speed improvements, orders of magnitude faster than existing tools.
- SpEED generates higher quality seeds compared to current leading software.
Conclusions:
- SpEED represents a significant advancement in spaced seed computation for bioinformatics.
- The software offers superior performance in terms of speed and sensitivity.
- SpEED is a valuable tool for various bioinformatics applications requiring efficient similarity search.
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